Open data for assessing habitats degree of conservation at plot level. An example dataset of forest structural attributes in Val d'Agri (Basilicata, Southern Italy)

Forests supply multiple ecosystem services and host a large proportion of the Earth's terrestrial biodiversity. In particular, they provide habitats for many taxonomic groups which can be threatened by forest unsustainable management practices. Type and intensity of forest management are widely recognized as the main drivers of structure and functions in forests ecosystems. However, to better understand the impacts and the benefits deriving from forest management, there is a big need to standardize procedures of field data collection and data analysis. Here, we provide a georeferenced dataset of vertical and horizontal structure of forest types belonging to 4 habitat types, sensu Council Directive 92/43/EEC. The dataset includes structural indicators commonly linked to old-growth forests in Europe, in particular the amount of standing and lying deadwood. We collected data on 32 plots (24 of 225 m2, and 8 of 100 m2, according to different forests type) during spring and summer of 2022, in Val d'Agri (Basilicata, Southern Italy). The dataset we provide follows the common national standard for field data collection in forest habitat types, published by ISPRA in 2016 with the aim to promote a greater homogeneity in assessment of habitat conservation status at Country and biogeographical level, as requested by the Habitats Directive.


a b s t r a c t
Forests supply multiple ecosystem services and host a large proportion of the Earth's terrestrial biodiversity. In particular, they provide habitats for many taxonomic groups which can be threatened by forest unsustainable management practices. Type and intensity of forest management are widely recognized as the main drivers of structure and functions in forests ecosystems. However, to better understand the impacts and the benefits deriving from forest management, there is a big need to standardize procedures of field data collection and data analysis. Here, we provide a georeferenced dataset of vertical and horizontal structure of forest types belonging to 4 habitat types, sensu Council Directive 92/43/EEC. The dataset includes structural indicators commonly linked to old-growth forests in Europe, in particular the amount of standing and lying deadwood. We collected data on 32 plots (24 of 225 m 2 , and 8 of 100 m 2 , according to different forests type) during spring and summer of 2022, in Val d'Agri (Basilicata, Southern Italy). The dataset we provide follows the common national standard for field data collection in forest habitat types, published by ISPRA in 2016 with the aim to promote a greater homogeneity in assessment of habitat conservation status at Country and biogeographical level, as requested by the Habitats Directive. ©

Value of the Data
• This dataset represents a monitoring baseline for the main forest habitat type in the Basilicata Region. • If integrated with other dataset, for example the one provided by Parisi et al [2] , where data for Basilicata Region are missing, the dataset can contribute to: 1) better understand the variability of the forest structural attributes in Central and Southern Italy and 2) produce the Favourable Reference Value for a list of indicators of forest ecosystems, based on real data, following the European Commission guidelines [3 , 4] . • The release of this dataset promotes the collaboration among researchers, monitoring and management Institutions (Administrative Regions, Regional Agencies for the Protection of the Environment). • The active involvement of ARPA Basilicata in field data collection ensures future repeating assessments in the same localities, to evaluate the trends over time and space. • This dataset represents a first practical example of standardization and homogenization of forest stand structure data collection for Habitat Monitoring sensu art. 17 of the Directive 92/43/EEC (hereafter Habitats Directive).
• Metadata will be used as a reference standard for Administrative Regions in our Country, since they derived from the National Handbook of Habitat Monitoring [5] , integrated with more recent literature. Moreover, metadata will support the development of practical indications for the correct application of the monitoring techniques recommended by National Guidelines for Habitat Monitoring [5] . The main stakeholder will be the National System for the Protection of the Environment (SNPA), but all the bodies involved in environmental monitoring activities will also benefit.

Objective
With the release of the dataset, ISPRA, in collaboration with ARPA Basilicata, decided to practically test on the field how Administrative Regions, which are responsible for habitat monitoring activities, can collect data on forests structure easily but efficiently. At the end of the project, IS-PRA will produce practical indications for the correct application of the monitoring techniques recommended by the National Handbook of Habitat Monitoring [5] . Table 1 shows the characteristics of the sample sites, and information on type of management, when available, as follows. The same information included in Table 1 are also reported in the shapefile that locates the sample sites. Table 2 provides the description and the measuring unit of all the attributes included in the dataset at plot level. It includes parameters used for assessing old-growth forests [6][7][8] , linking them to the main type forests management, in order to both select indicators useful for assessing the conservation degree of forest habitat types, and identify good practices for nature conservation in these ecosystems. Litter cover ( < 2 cm depth) % C_litter2

Data Description
Litter cover ( > 2 cm depth) % C_T1 Tree high layer cover % C_T2 Tree low layer cover % C_SH1 Shrub high layer cover % C_SH2 Shrub low layer cover % C_herb Herb layer cover % C_J Juvenile layer cover % C_S Seedlings layers cover % H_T1_max Max tree high layer height m H_T1_avg Mean tree high layer height m H_T2_max Max tree low layer height m H_T2_avg Mean tree low layer height m H_SH1_max Max shrub high layer height m H_SH1_avg Mean shrub high layer height m H_SH2_max Max shrub low layer height m H_SH2_avg Mean shrub low layer height m H_herb_max Max herb layer height m H_herb_avg Mean herb ayer height m Epyphytes Epiphytes occurrence (present, abundant, absent) Non_vasc Lichens and mosses occurrence (present, abundant, absent) Table 2 contains information on structure at plot level. Table 3 contains information on living trees and deadwood at plot level.   Table 4 describes the dataset related to single-tree data, and it contains the following fields for all living trees, exceeding 10 cm DBH, occurring in the plots. The nomenclature follows [9 , 10] : Along the slopes, area mainly hosts Quercus cerris dominated forests, which is the most spread woods in Basilicata Region; in the South-Eastern part of the area, close to the Pertusillo Lake, the main ecosystems are represented by mixed oak forests ( Quercus cerris and Quercus frainetto , belonging to the habitat 91M0); Q. pubescens is relatively rare in the area and it is not associated to any habitat type. Fagus sylvatica forests (habitat 9210 * ) can only be found in Viggiano Mountain and Aquila Mountain. Among the azonal forests, two riverine woods can be identified, the first one dominated by Populus nigra and/or Salix alba (habitat 92A0), the second one characterized by Alnus glutinosa (belonging to the habitat 91E0) [11 , 12] . Furthermore, the area hosts one of the main centers of Oil exploitation in Basilicata and in Italy. Fig. 1 shows the investigated area and the location of sample sites. We used a random-stratified sampling design according to the different forest ecosystem types recognized in the Map of the Nature, a national project for land management and environmental protection produced by ISPRA for each administrative region. The Basilicata Map of the Nature was released in 2012 at a scale of 1:50.0 0 0 [13] , and it includes a total of 86 habitat types and, in particular, 23 forest habitat types. Each landscape unit (polygon) in the Map of the Nature is also associated to an assessment of the "ecological value" [14] , defined as a "naturalistic quality", calculated through the use of specific indicators and applied at regional level [15] . We used the attribute "ecological value" as a proxy of the human impact that occurs in each forest polygon within the study area.

Experimental Design, Materials and Methods
The selection of the location of the sample sites were spatially balanced by using the software QGis vers. 3.22 [16] . Environmental data of the sample sites ( = plots) are shown in Table 1 .
Sample sites were located in the field by using GPS in order to identify the centre of the plot. Plots have square shape (225 m 2 ) in zonal forests ( Quercus or Fagus dominated forests); and rectangular shape (100 m 2 i.e., 20 m × 5 m) in azonal riparian forests ( Salix, Populus or Alnus dominated forests). Shapes and dimensions, follow the standards of National and European Handbook for habitat monitoring activities [5 , 17] .
In each plot, we recorded, by visual assessment, the percentage cover of deadwood, and percentage cover of living trees. Particularly, we collected the percentage cover of each vegetation layer (included juvenile and seedlings, which are in general neglected compared to the other layers but are indeed important as surrogate of the resilience of the forests), the highest and average heights of trees, shrubs, and herbs layers. We also measured the DBH of living trees at individual level by using meter sticks. Finally, we recorded the number of standing dead trees, downed dead trees, stumps, snags, old trees, and trees with cavities per plot ( Table 3 ).
Visual estimates are often applied in vegetation cover studies as they are relatively rapid and well established, although potentially less robust than other methods; to reduce the degree of subjectivity data were collected by a unit of only 4 researchers in a very short period (from May to July 2022).
For future monitoring activities, we suggest the use of innovative technologies such as laser scanner, in order to provide more accurate measurements for the assessment at the national spatial scale.
Concerning data collection, we use standardized field survey forms, and "VegApp", a free application on Android platform ( https://vegapp.de/ ), which allows to collect structural and vegetation data on the field, storing them directly in a georeferenced database.
Lastly, in order to stress the importance of forests management plans to provide useful data for the assessment of conservation status of the habitat types [18] , we recorded the type of management, according to forestry management plans available for two of the involved Municipalities, Viggiano and Grumento Nova, ( http://valutazioneambientale.regione.basilicata.it/ valutazioneambie/detail.jsp?sec=104357&otype=1011&id=104976 , http://valutazioneambientale. regione.basilicata.it/valutazioneambie/detail.jsp?sec=102944&otype=1011&id=103612 ; accessed 05/12/2022). Forestry management plans still lack for some Municipalities. In this case, we indicated the type of management according to field survey observations.

Ethics Statements
The authors declare that the present work did not include experiments on human subjects and/or animals.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data Availability
Open data for assessing habitats degree of conservation at plot level. An example dataset of forest structural attributes in Val d'Agri (Basilicata, Southern Italy) (Original data) (Zenodo).